Data regarding an object is acquired and analyzed to generate a result in many cases. For example, a motion sensor is attached to a moving object and data about a sensed motion of the moving object is acquired and analyzed to generate predetermined information about the motion of the object, or image data about the moving object is acquired and analyzed to create predetermined information about the motion of the object.
Acquisition of data regarding an object and generation of a result using the data are used for sports motion analysis and the like.
For example, there is a case in which predetermined data regarding a golf swing of a user is acquired and a result is generated using the data, as illustrated in FIG. 1.
Specifically, as shown in FIG. 1, it is possible to provide information about a golf swing motion of the user U and a motion of a golf club during golf swing to the user as an integrated result by photographing a golf swing of the user U with the golf club GC to acquire image data about the golf swing motion of the user, obtaining motion sensing data about the golf swing through a motion sensing device MSD attached to the golf club GC, and representing the motion of the golf club GC, acquired by the motion sensing device MSD, along with a golf swing motion image of the user.
Here, an image acquired by a camera device 10 is delivered to an image processing device 20, data acquired through the motion sensing device MSD is wirelessly transmitted to a motion sensing data processing device 30 and then delivered to the image processing device 20, and a predetermined image is generated from the image data and the motion sensing data in the image processing device 20 and displayed through a display device 40, as illustrated in FIG. 1.
Examples of images displayed through the aforementioned method are shown in FIG. 3. Here, there is a difference between an image data sampling rate and a motion sensing data sampling rate, and thus unnatural images are provided.
FIG. 2 shows sampling time of image data and motion sensing data which are sampled through the system as illustrated in FIG. 1. In this case, it is very difficult to use the image data and the motion sensing data as data about the same time due to a remarkable difference between a sampling rate of the camera device and a sampling rate of the motion sensing device.
In general, the motion sensing device including an acceleration sensor, a gyro sensor or the like acquires data hundreds or thousands of times per second, whereas the camera device acquires an image of scores of frames per second. Even a high-speed camera or super-high-speed camera acquires hundreds of frames per second. Accordingly, it is difficult to obtain data regarding the same time through the motion sensing device and the camera device due to a data acquisition time difference between the motion sensing device and the camera device.
As shown in FIG. 2, when the image data sampling time is T1, T2, T3, . . . , an image data sampling interval is ΔT, the motion sensing data sampling time is t1, t2, t3, . . . and a motion sensing data sampling interval is Δt, very unnatural images are obtained as illustrated in FIG. 3 since there is a large difference between ΔT and Δt.
Images of a consecutive golf swing motion of the user are shown in (a) to (h) of FIG. 3. Here, an object SO overlapping each image is based on motion sensing data acquired by the motion sensing device attached to the golf club of the user.
In FIG. 3, (a) to (d) show identical image data sampled at a certain time and (e) to (h) show identical image data sampled at the next time. The objects SO according to the motion sensing data, shown in (a) to (h), are based on data sampled at different times.
That is, while the image data shown in FIG. 3(a) is acquired and then the image data shown in FIG. 3(e) is obtained, motion sensing data is obtained as illustrated in (a), (b), (c) and (d) of FIG. 3 and then motion sensing data is obtained as illustrated in (e), (f), (g) and (h) of FIG. 3.
When the still images shown in (a) to (h) of FIG. 3 are reproduced as a moving image, the images are not matched with the objects SO and thus an unnatural image is reproduced.
Although FIGS. 1 to 3 exemplify image data and motion sensing data, it is difficult to acquire synchronized data between different types of devices which acquire different types of data other than the image data and motion sensing data due to a sampling time difference between the devices. Accordingly, it is difficult to use data acquired by the respective devices for the same result in many cases.
For example, when images as shown in FIG. 3 are generated using image data regarding a golf swing of a user and motion sensing data acquired by a motion sensing device attached to the head of the user, an unnatural image, in which an object (e.g., an object indicating the head of the user using a circle) displayed based on the motion sensing data moves while the head of the user does not move, is generated.